scholarly journals Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis

PLoS Biology ◽  
2019 ◽  
Vol 17 (5) ◽  
pp. e3000265 ◽  
Author(s):  
Joshua L. Payne ◽  
Fabrizio Menardo ◽  
Andrej Trauner ◽  
Sonia Borrell ◽  
Sebastian M. Gygli ◽  
...  

2018 ◽  
Author(s):  
Joshua L. Payne ◽  
Fabrizio Menardo ◽  
Andrej Trauner ◽  
Sonia Borrell ◽  
Sebastian M. Gygli ◽  
...  

AbstractTransition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of mutations spreading under relaxed selection. However, demonstrating the role of transition bias in adaptive evolution remains challenging. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis. We found strong evidence for transition bias in two independently curated datasets comprising 152 and 208 antibiotic resistance mutations. This was true at the level of mutational paths (distinct, adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes), and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the ribosmal gene rrs), and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.Significance statementWhether and how transition bias influences adaptive evolution remain open questions. We studied 296 DNA mutations that confer antibiotic resistance to the human pathogen Mycobacterium tuberculosis. We uncovered strong transition bias among these mutations and also among the number of times each mutation has evolved in different strains or geographic locations, demonstrating that transition bias can influence adaptive evolution. For a subset of mutations, we were able to rule out an alternative selection-based hypothesis for this bias, indicating that transition bias can be caused by a biased mutation supply. By revealing this bias among M. Tuberculosis resistance mutations, our findings improve our ability to predict the mutational pathways by which pathogens overcome treatment.



FEBS Journal ◽  
2016 ◽  
Vol 283 (12) ◽  
pp. 2206-2218 ◽  
Author(s):  
Ekaterina V. Filippova ◽  
Karen J. Kieser ◽  
Chi-Hao Luan ◽  
Zdzislaw Wawrzak ◽  
Olga Kiryukhina ◽  
...  


Microbiology ◽  
2000 ◽  
Vol 146 (4) ◽  
pp. 1011-1018 ◽  
Author(s):  
F. Bigi ◽  
A. Alito ◽  
M. I. Romano ◽  
M. Zumarraga ◽  
K. Caimi ◽  
...  


PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5895 ◽  
Author(s):  
Thomas Andreas Kohl ◽  
Christian Utpatel ◽  
Viola Schleusener ◽  
Maria Rosaria De Filippo ◽  
Patrick Beckert ◽  
...  

Analyzing whole-genome sequencing data of Mycobacterium tuberculosis complex (MTBC) isolates in a standardized workflow enables both comprehensive antibiotic resistance profiling and outbreak surveillance with highest resolution up to the identification of recent transmission chains. Here, we present MTBseq, a bioinformatics pipeline for next-generation genome sequence data analysis of MTBC isolates. Employing a reference mapping based workflow, MTBseq reports detected variant positions annotated with known association to antibiotic resistance and performs a lineage classification based on phylogenetic single nucleotide polymorphisms (SNPs). When comparing multiple datasets, MTBseq provides a joint list of variants and a FASTA alignment of SNP positions for use in phylogenomic analysis, and identifies groups of related isolates. The pipeline is customizable, expandable and can be used on a desktop computer or laptop without any internet connection, ensuring mobile usage and data security. MTBseq and accompanying documentation is available from https://github.com/ngs-fzb/MTBseq_source.



2019 ◽  
Vol 133 (12) ◽  
pp. 1271-1280 ◽  
Author(s):  
Stefan H. Oehlers

Abstract The spectre of the coming post-antibiotic age demands novel therapies for infectious diseases. Tuberculosis (TB), caused by Mycobacterium tuberculosis, is the single deadliest infection throughout human history. M. tuberculosis has acquired antibiotic resistance at an alarming rate with some strains reported as being totally drug resistant. Host-directed therapies (HDTs) attempt to overcome the evolution of antibiotic resistance by targeting relatively immutable host processes. Here, I hypothesise the induction of hypoxia via anti-angiogenic therapy will be an efficacious HDT against TB. I argue that anti-angiogenic therapy is a modernisation of industrial revolution era sanatoria treatment for TB, and present a view of the TB granuloma as a ‘bacterial tumour’ that can be treated with anti-angiogenic therapies to reduce bacterial burden and spare host immunopathology. I suggest two complementary modes of action, induction of bacterial dormancy and activation of host hypoxia-induced factor (HIF)-mediated immunity, and define the experimental tools necessary to test this hypothesis.





Sign in / Sign up

Export Citation Format

Share Document